The sky view factor (SVF) has an important role in the analysis of the urban micro-climate. A new vector-based SVF calculation tool was implemented in a free and open source Geographic Information System named OrbisGIS. Its accuracy and computational performance are compared to the ones of an existing raster based algorithm used in SAGA-GIS. The study is performed on 72 urban blocks selected within the Paris commune territory. This sample has been chosen to represent the heterogeneity of nine of the ten Local Climate Zone built types. The effect of the algorithms’ input parameters (ray length, number of directions and grid resolution) is investigated. The combination minimizing the computation time and the SVF error is identified for SAGA-GIS and OrbisGIS algorithms. In both cases, the standard deviation of the block mean SVF estimate is about 0.03. A simple linear relationship having a high determination coefficient is also established between block mean SVF and the facade density fraction, confirming the results of previous research. This formula and the optimized combinations for the OrbisGIS and the SAGA-GIS algorithms are finally used to calculate the SVF of every urban block of the Paris commune.

The urbanisation phenomenon and related cities expansion and transport networks entail preventing the increase of population exposed to environmental pollution. Regarding noise exposure, the Environmental Noise Directive demands on main metropolis to produce noise maps. While based on standard methods, these latter are usually generated by proprietary software and require numerous input data concerning, for example, the buildings, land use, transportation network and traffic. The present work describes an open source implementation of a noise mapping tool fully implemented in a Geographic Information System compliant with the Open Geospatial Consortium standards. This integration makes easier at once the formatting and harvesting of noise model input data, cartographic rendering and output data linkage with population data. An application is given for a French city, which consists in estimating the impact of road traffic-related scenarios in terms of population exposure to noise levels in relation to both a threshold value and level classes.